Firstly, you should write to the CG mailing list instead of CC'ing us all - https://groups.google.com/forum/#!forum/constraint-grammar / [email protected] - I have done so with this reply.
Anyway, I have been saying this for a long time. The past decade of machine learning has simply approached the hand-written method. E.g., when Google published https://research.googleblog.com/2016/05/announcing-syntaxnet-worlds-most.html my immediate comment was: Their induced rules smell an awful lot like constraint grammar, just expressed in vector fields. Other papers in the field even explicitly say that their models look a lot more like classic systems, with separate source language analysis, transfer, and target language generation. And this holds for any text-to-text transformation, not just translation. So I am not the least bit surprised that more advanced models look more and more like rule-based systems. -- Tino Didriksen On Wed, 26 Feb 2020 at 14:26, Tiedemann, Jörg <[email protected]> wrote: > Dear CG community, > > > I am reaching out to you because we have the idea to follow-up on Anssi > Yli-Jyrä’s ideas on comparing CG to transformer models to see whether there > is some commonalities between expert-made linguistic grammars and learned > neural language models. This is some kind of fascinating question and we > would like to carry out some empirical studies to find possible > correlations and patterns. > > It would be great to get an update about available CG resources to get > started and it would also be interesting to hear whether anyone of you > would be interested to even collaborate in that study. What I had in mind > was to look into the disambiguation process done on real-world data using > CG-based parsers and compare that with the activations triggered in trained > neural language models. > > It would be excellent to know whether there are some (hopefully freely > available) wide-coverage grammars and parsers available that we can study. > Most likely, we need to look into high-resource languages (including > Finnish( to also make proper comparisons to neural models but other > scenarios are possible as well. Please, let me and Anssi know whether you > have any suggestions. Thanks a ot! > > > All the best, > Jörg > -- You received this message because you are subscribed to the Google Groups "Constraint Grammar" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/constraint-grammar/CABnmVq6rpbp1-hDsk6VWLb5YOAXdWgu8UDcXwb4rzxrLCY592A%40mail.gmail.com.
